Examining the impact of cognitive load on structure learning
6 agents, 12 issues
Method changes:
0
|
0.25
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0.5
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0.75
|
1
|
Overall
|
|
|---|---|---|---|---|---|---|
| high (N=21) |
high (N=22) |
high (N=22) |
high (N=15) |
high (N=15) |
high (N=95) |
|
| age | ||||||
| Mean (SD) | 37.7 (11.3) | 35.6 (11.7) | 39.5 (13.3) | 34.5 (11.5) | 42.7 (12.2) | 37.9 (12.1) |
| Median [Min, Max] | 37.0 [20.0, 61.0] | 34.0 [19.0, 61.0] | 37.5 [20.0, 69.0] | 34.0 [18.0, 55.0] | 39.0 [27.0, 67.0] | 36.0 [18.0, 69.0] |
| race | ||||||
| Asian | 2 (9.5%) | 3 (13.6%) | 4 (18.2%) | 1 (6.7%) | 0 (0%) | 10 (10.5%) |
| Black or African-American | 4 (19.0%) | 2 (9.1%) | 4 (18.2%) | 4 (26.7%) | 0 (0%) | 14 (14.7%) |
| Hispanic/Latinx | 1 (4.8%) | 0 (0%) | 1 (4.5%) | 2 (13.3%) | 0 (0%) | 4 (4.2%) |
| White | 14 (66.7%) | 17 (77.3%) | 12 (54.5%) | 8 (53.3%) | 15 (100%) | 66 (69.5%) |
| American Indian or Alaska Native | 0 (0%) | 0 (0%) | 1 (4.5%) | 0 (0%) | 0 (0%) | 1 (1.1%) |
| gender | ||||||
| Man | 11 (52.4%) | 13 (59.1%) | 8 (36.4%) | 7 (46.7%) | 4 (26.7%) | 43 (45.3%) |
| Non-binary | 1 (4.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (1.1%) |
| Woman | 9 (42.9%) | 9 (40.9%) | 14 (63.6%) | 8 (53.3%) | 10 (66.7%) | 50 (52.6%) |
| Prefer not to answer | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (6.7%) | 1 (1.1%) |
| matrix_acc | ||||||
| Mean (SD) | 0.863 (0.181) | 0.835 (0.170) | 0.744 (0.274) | 0.758 (0.285) | 0.600 (0.280) | 0.771 (0.248) |
| Median [Min, Max] | 0.875 [0.250, 1.00] | 0.875 [0.250, 1.00] | 0.875 [0, 1.00] | 0.875 [0, 1.00] | 0.625 [0, 1.00] | 0.875 [0, 1.00] |
| as.factor(matrix_n_correct) | ||||||
| 0 | 0 (0%) | 0 (0%) | 2 (9.1%) | 1 (6.7%) | 1 (6.7%) | 4 (4.2%) |
| 2 | 1 (4.8%) | 1 (4.5%) | 0 (0%) | 1 (6.7%) | 2 (13.3%) | 5 (5.3%) |
| 3 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (6.7%) | 1 (1.1%) |
| 4 | 0 (0%) | 0 (0%) | 2 (9.1%) | 0 (0%) | 1 (6.7%) | 3 (3.2%) |
| 5 | 1 (4.8%) | 1 (4.5%) | 0 (0%) | 1 (6.7%) | 4 (26.7%) | 7 (7.4%) |
| 6 | 4 (19.0%) | 6 (27.3%) | 6 (27.3%) | 4 (26.7%) | 2 (13.3%) | 22 (23.2%) |
| 7 | 6 (28.6%) | 8 (36.4%) | 9 (40.9%) | 4 (26.7%) | 3 (20.0%) | 30 (31.6%) |
| 8 | 9 (42.9%) | 6 (27.3%) | 3 (13.6%) | 4 (26.7%) | 1 (6.7%) | 23 (24.2%) |
0.25
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0.5
|
0.75
|
1
|
Overall
|
|
|---|---|---|---|---|---|
| high (N=1) |
high (N=1) |
high (N=2) |
high (N=2) |
high (N=6) |
|
| age | |||||
| Mean (SD) | 45.0 (NA) | 28.0 (NA) | 39.0 (1.41) | 21.0 (2.83) | 32.2 (10.3) |
| Median [Min, Max] | 45.0 [45.0, 45.0] | 28.0 [28.0, 28.0] | 39.0 [38.0, 40.0] | 21.0 [19.0, 23.0] | 33.0 [19.0, 45.0] |
| race | |||||
| American Indian or Alaska Native | 1 (100%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (16.7%) |
| White | 0 (0%) | 1 (100%) | 1 (50.0%) | 2 (100%) | 4 (66.7%) |
| Black or African-American | 0 (0%) | 0 (0%) | 1 (50.0%) | 0 (0%) | 1 (16.7%) |
| gender | |||||
| Woman | 1 (100%) | 1 (100%) | 1 (50.0%) | 1 (50.0%) | 4 (66.7%) |
| Man | 0 (0%) | 0 (0%) | 1 (50.0%) | 1 (50.0%) | 2 (33.3%) |
| matrix_acc | |||||
| Mean (SD) | 1.00 (NA) | 0.625 (NA) | 0.750 (0.177) | 0.938 (0.0884) | 0.833 (0.171) |
| Median [Min, Max] | 1.00 [1.00, 1.00] | 0.625 [0.625, 0.625] | 0.750 [0.625, 0.875] | 0.938 [0.875, 1.00] | 0.875 [0.625, 1.00] |
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: corrresp
Chisq Df Pr(>Chisq)
opinion_round 33.0185 1 9.129e-09 ***
Deviant_threshold 10.4791 4 0.03309 *
opinion_round:Deviant_threshold 4.2958 4 0.36746
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 1 opinion_round.trend SE df asymp.LCL asymp.UCL z.ratio p.value
overall 0.139 0.0237 Inf 0.0924 0.185 5.858 <.0001
Results are averaged over the levels of: Deviant_threshold
Confidence level used: 0.95 $emmeans
Deviant_threshold emmean SE df asymp.LCL asymp.UCL z.ratio p.value
0 1.537 0.168 Inf 1.207 1.87 9.140 <.0001
0.25 1.199 0.163 Inf 0.880 1.52 7.371 <.0001
0.5 1.073 0.160 Inf 0.758 1.39 6.687 <.0001
0.75 0.898 0.193 Inf 0.521 1.28 4.661 <.0001
1 1.560 0.200 Inf 1.169 1.95 7.816 <.0001
Results are given on the logit (not the response) scale.
Confidence level used: 0.95
$contrasts
contrast estimate SE df asymp.LCL
Deviant_threshold0 - Deviant_threshold0.25 0.3382 0.232 Inf -0.2954
Deviant_threshold0 - Deviant_threshold0.5 0.4644 0.231 Inf -0.1644
Deviant_threshold0 - Deviant_threshold0.75 0.6388 0.254 Inf -0.0545
Deviant_threshold0 - Deviant_threshold1 -0.0233 0.259 Inf -0.7300
Deviant_threshold0.25 - Deviant_threshold0.5 0.1262 0.227 Inf -0.4921
Deviant_threshold0.25 - Deviant_threshold0.75 0.3006 0.251 Inf -0.3834
Deviant_threshold0.25 - Deviant_threshold1 -0.3614 0.256 Inf -1.0589
Deviant_threshold0.5 - Deviant_threshold0.75 0.1744 0.249 Inf -0.5057
Deviant_threshold0.5 - Deviant_threshold1 -0.4877 0.254 Inf -1.1814
Deviant_threshold0.75 - Deviant_threshold1 -0.6621 0.276 Inf -1.4149
asymp.UCL z.ratio p.value
0.9717 1.456 0.5913
1.0932 2.015 0.2589
1.3320 2.513 0.0876
0.6835 -0.090 1.0000
0.7445 0.557 0.9811
0.9847 1.199 0.7521
0.3360 -1.414 0.6188
0.8545 0.699 0.9567
0.2060 -1.918 0.3078
0.0908 -2.399 0.1155
Results are given on the log odds ratio (not the response) scale.
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 5 estimates
P value adjustment: tukey method for comparing a family of 5 estimates Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
targetpair 528.5 528.5 1 95 2.2408 0.1377
Deviant_threshold 17044.1 17044.1 1 95 72.2623 2.624e-13 ***
targetpair:Deviant_threshold 14921.1 14921.1 1 95 63.2612 3.768e-12 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1$emtrends
targetpair Deviant_threshold.trend SE df lower.CL upper.CL t.ratio p.value
DN -61.32 5.64 95 -72.5 -50.13 -10.878 <.0001
NN -5.56 4.87 95 -15.2 4.12 -1.140 0.2571
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio p.value
DN - NN -55.8 7.01 95 -69.7 -41.8 -7.954 <.0001
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95 # A tibble: 2 × 13
model term estimate std.error statistic p.value conf.low
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 below_.5 Deviant_threshold -21.5 9.64 -2.23 0.0292 -40.8
2 above_.5 Deviant_threshold 4.22 11.2 0.376 0.709 -18.3
conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <int> <int>
1 -2.25 0.0733 0.0585 1 63 65
2 26.8 0.00282 -0.0171 1 50 52# A tibble: 2 × 13
model term estimate std.error statistic p.value conf.low
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 below_.5 Deviant_threshold -11.2 17.6 -0.637 0.526 -46.4
2 above_.5 Deviant_threshold -3.53 14.7 -0.240 0.811 -33.1
conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <int> <int>
1 24.0 0.00640 -0.00937 1 63 65
2 26.1 0.00115 -0.0188 1 50 52Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 1469 367.14 0.5063 0.7312
Residuals 90 65258 725.09 $emmeans
deviance emmean SE df lower.CL upper.CL t.ratio p.value
0 52.4 5.88 90 40.7 64.1 8.914 <.0001
0.25 55.3 5.74 90 43.9 66.7 9.628 <.0001
0.5 46.9 5.74 90 35.5 58.3 8.163 <.0001
0.75 46.8 6.95 90 33.0 60.6 6.731 <.0001
1 45.0 6.95 90 31.2 58.8 6.472 <.0001
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio p.value
deviance0 - deviance0.25 -2.8918 8.22 90 -25.8 20.0 -0.352 0.9967
deviance0 - deviance0.5 5.5173 8.22 90 -17.4 28.4 0.672 0.9620
deviance0 - deviance0.75 5.5810 9.10 90 -19.8 30.9 0.613 0.9727
deviance0 - deviance1 7.3810 9.10 90 -18.0 32.7 0.811 0.9267
deviance0.25 - deviance0.5 8.4091 8.12 90 -14.2 31.0 1.036 0.8381
deviance0.25 - deviance0.75 8.4727 9.02 90 -16.6 33.6 0.940 0.8806
deviance0.25 - deviance1 10.2727 9.02 90 -14.8 35.4 1.139 0.7852
deviance0.5 - deviance0.75 0.0636 9.02 90 -25.0 25.2 0.007 1.0000
deviance0.5 - deviance1 1.8636 9.02 90 -23.2 27.0 0.207 0.9996
deviance0.75 - deviance1 1.8000 9.83 90 -25.6 29.2 0.183 0.9997
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 5 estimates
P value adjustment: tukey method for comparing a family of 5 estimates | 0 (N=21) |
0.25 (N=22) |
0.5 (N=22) |
0.75 (N=15) |
1 (N=15) |
Overall (N=95) |
|
|---|---|---|---|---|---|---|
| pred_maj | ||||||
| Yes | 4 (19.0%) | 5 (22.7%) | 3 (13.6%) | 3 (20.0%) | 1 (6.7%) | 16 (16.8%) |
| No | 17 (81.0%) | 17 (77.3%) | 19 (86.4%) | 12 (80.0%) | 14 (93.3%) | 79 (83.2%) |
# A tibble: 4 × 14
# Groups: pred_maj [2]
pred_maj id term estimate std.error statistic p.value
<lgl> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 FALSE below_.5 Deviant_threshold -10.4 19.0 -0.550 0.584
2 FALSE above_.5 Deviant_threshold -5.85 15.1 -0.389 0.700
3 TRUE below_.5 Deviant_threshold -26.2 44.7 -0.585 0.571
4 TRUE above_.5 Deviant_threshold -2.00 53.2 -0.0376 0.971
conf.low conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
1 -48.5 27.6 0.00590 -0.0136 1 51 53
2 -36.2 24.5 0.00350 -0.0197 1 43 45
3 -126. 73.5 0.0331 -0.0636 1 10 12
4 -139. 135. 0.000283 -0.200 1 5 7Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 1469 367.1 0.5073 0.73048
pred_maj 1 3512 3511.7 4.8522 0.03032 *
deviance:pred_maj 4 228 57.1 0.0789 0.98857
Residuals 85 61518 723.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1| 0 (N=21) |
0.25 (N=22) |
0.5 (N=22) |
0.75 (N=15) |
1 (N=15) |
Overall (N=95) |
|
|---|---|---|---|---|---|---|
| pns_med | ||||||
| High | 10 (47.6%) | 8 (36.4%) | 10 (45.5%) | 9 (60.0%) | 8 (53.3%) | 45 (47.4%) |
| Low | 10 (47.6%) | 14 (63.6%) | 12 (54.5%) | 6 (40.0%) | 7 (46.7%) | 49 (51.6%) |
| Missing | 1 (4.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (1.1%) |
# A tibble: 4 × 14
# Groups: pns_med [2]
pns_med id term estimate std.error statistic p.value
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 High below_.5 Deviant_threshold 5.20 25.5 0.204 0.840
2 High above_.5 Deviant_threshold -2.94 20.5 -0.143 0.887
3 Low below_.5 Deviant_threshold -31.5 25.2 -1.25 0.220
4 Low above_.5 Deviant_threshold -8.04 20.8 -0.387 0.703
conf.low conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
1 -47.3 57.7 0.00159 -0.0368 1 26 28
2 -45.2 39.3 0.000821 -0.0391 1 25 27
3 -82.8 19.7 0.0439 0.0158 1 34 36
4 -51.1 35.0 0.00646 -0.0367 1 23 25Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 1623 405.75 0.5444 0.7036
pns_med 1 305 304.61 0.4087 0.5244
deviance:pns_med 4 1670 417.48 0.5601 0.6922
Residuals 84 62607 745.33 | 0 (N=95) |
1 (N=95) |
2 (N=95) |
3 (N=95) |
4 (N=95) |
5 (N=95) |
6 (N=95) |
7 (N=95) |
Overall (N=760) |
|
|---|---|---|---|---|---|---|---|---|---|
| trialnum | |||||||||
| 0 | 18 (18.9%) | 18 (18.9%) | 16 (16.8%) | 16 (16.8%) | 10 (10.5%) | 14 (14.7%) | 12 (12.6%) | 12 (12.6%) | 116 (15.3%) |
| 1 | 16 (16.8%) | 19 (20.0%) | 10 (10.5%) | 8 (8.4%) | 15 (15.8%) | 13 (13.7%) | 15 (15.8%) | 11 (11.6%) | 107 (14.1%) |
| 2 | 9 (9.5%) | 9 (9.5%) | 10 (10.5%) | 8 (8.4%) | 9 (9.5%) | 6 (6.3%) | 11 (11.6%) | 15 (15.8%) | 77 (10.1%) |
| 3 | 12 (12.6%) | 10 (10.5%) | 18 (18.9%) | 15 (15.8%) | 11 (11.6%) | 17 (17.9%) | 12 (12.6%) | 14 (14.7%) | 109 (14.3%) |
| 4 | 15 (15.8%) | 10 (10.5%) | 10 (10.5%) | 15 (15.8%) | 13 (13.7%) | 16 (16.8%) | 7 (7.4%) | 9 (9.5%) | 95 (12.5%) |
| 5 | 8 (8.4%) | 12 (12.6%) | 10 (10.5%) | 13 (13.7%) | 12 (12.6%) | 11 (11.6%) | 19 (20.0%) | 15 (15.8%) | 100 (13.2%) |
| 6 | 10 (10.5%) | 8 (8.4%) | 8 (8.4%) | 12 (12.6%) | 12 (12.6%) | 11 (11.6%) | 10 (10.5%) | 7 (7.4%) | 78 (10.3%) |
| 7 | 7 (7.4%) | 9 (9.5%) | 13 (13.7%) | 8 (8.4%) | 13 (13.7%) | 7 (7.4%) | 9 (9.5%) | 12 (12.6%) | 78 (10.3%) |
0
|
0.25
|
0.5
|
0.75
|
1
|
Overall
|
|
|---|---|---|---|---|---|---|
| low (N=15) |
low (N=25) |
low (N=20) |
low (N=15) |
low (N=16) |
low (N=91) |
|
| age | ||||||
| Mean (SD) | 35.3 (11.3) | 39.3 (8.77) | 38.6 (12.8) | 36.5 (12.3) | 34.7 (13.9) | 37.2 (11.6) |
| Median [Min, Max] | 33.0 [22.0, 59.0] | 37.0 [28.0, 57.0] | 37.5 [20.0, 63.0] | 38.0 [20.0, 61.0] | 27.5 [19.0, 62.0] | 35.0 [19.0, 63.0] |
| race | ||||||
| Asian | 2 (13.3%) | 2 (8.0%) | 4 (20.0%) | 3 (20.0%) | 3 (18.8%) | 14 (15.4%) |
| Black or African-American | 1 (6.7%) | 2 (8.0%) | 1 (5.0%) | 2 (13.3%) | 1 (6.3%) | 7 (7.7%) |
| White | 12 (80.0%) | 17 (68.0%) | 14 (70.0%) | 9 (60.0%) | 11 (68.8%) | 63 (69.2%) |
| American Indian or Alaska Native | 0 (0%) | 1 (4.0%) | 0 (0%) | 0 (0%) | 1 (6.3%) | 2 (2.2%) |
| Hispanic/Latinx | 0 (0%) | 2 (8.0%) | 1 (5.0%) | 1 (6.7%) | 0 (0%) | 4 (4.4%) |
| Other | 0 (0%) | 1 (4.0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (1.1%) |
| gender | ||||||
| Man | 6 (40.0%) | 10 (40.0%) | 6 (30.0%) | 7 (46.7%) | 7 (43.8%) | 36 (39.6%) |
| Non-binary | 2 (13.3%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (2.2%) |
| Woman | 7 (46.7%) | 15 (60.0%) | 14 (70.0%) | 8 (53.3%) | 8 (50.0%) | 52 (57.1%) |
| Prefer not to answer | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (6.3%) | 1 (1.1%) |
| matrix_acc | ||||||
| Mean (SD) | 0.908 (0.0880) | 0.960 (0.0595) | 0.944 (0.0949) | 0.908 (0.0999) | 0.898 (0.131) | 0.929 (0.0953) |
| Median [Min, Max] | 0.875 [0.750, 1.00] | 1.00 [0.875, 1.00] | 1.00 [0.750, 1.00] | 0.875 [0.750, 1.00] | 0.938 [0.625, 1.00] | 1.00 [0.625, 1.00] |
| as.factor(matrix_n_correct) | ||||||
| 5 | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (12.5%) | 2 (2.2%) |
| 6 | 2 (13.3%) | 0 (0%) | 3 (15.0%) | 3 (20.0%) | 1 (6.3%) | 9 (9.9%) |
| 7 | 7 (46.7%) | 8 (32.0%) | 3 (15.0%) | 5 (33.3%) | 5 (31.3%) | 28 (30.8%) |
| 8 | 6 (40.0%) | 17 (68.0%) | 14 (70.0%) | 7 (46.7%) | 8 (50.0%) | 52 (57.1%) |
0
|
0.25
|
0.5
|
1
|
Overall
|
|
|---|---|---|---|---|---|
| low (N=1) |
low (N=1) |
low (N=1) |
low (N=4) |
low (N=7) |
|
| age | |||||
| Mean (SD) | 38.0 (NA) | 35.0 (NA) | 34.0 (NA) | 40.3 (10.6) | 38.3 (7.97) |
| Median [Min, Max] | 38.0 [38.0, 38.0] | 35.0 [35.0, 35.0] | 34.0 [34.0, 34.0] | 40.0 [29.0, 52.0] | 35.0 [29.0, 52.0] |
| race | |||||
| White | 1 (100%) | 1 (100%) | 0 (0%) | 2 (50.0%) | 4 (57.1%) |
| Hispanic/Latinx | 0 (0%) | 0 (0%) | 1 (100%) | 0 (0%) | 1 (14.3%) |
| Black or African-American | 0 (0%) | 0 (0%) | 0 (0%) | 2 (50.0%) | 2 (28.6%) |
| gender | |||||
| Woman | 1 (100%) | 0 (0%) | 0 (0%) | 3 (75.0%) | 4 (57.1%) |
| Man | 0 (0%) | 1 (100%) | 1 (100%) | 1 (25.0%) | 3 (42.9%) |
| matrix_acc | |||||
| Mean (SD) | 0.875 (NA) | 0.875 (NA) | 1.00 (NA) | 0.969 (0.0625) | 0.946 (0.0668) |
| Median [Min, Max] | 0.875 [0.875, 0.875] | 0.875 [0.875, 0.875] | 1.00 [1.00, 1.00] | 1.00 [0.875, 1.00] | 1.00 [0.875, 1.00] |
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: corrresp
Chisq Df Pr(>Chisq)
opinion_round 41.4648 1 1.2e-10 ***
Deviant_threshold 3.7914 4 0.4350
opinion_round:Deviant_threshold 4.9432 4 0.2932
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 1 opinion_round.trend SE df asymp.LCL asymp.UCL z.ratio p.value
overall 0.142 0.0223 Inf 0.0987 0.186 6.394 <.0001
Results are averaged over the levels of: Deviant_threshold
Confidence level used: 0.95 $emmeans
Deviant_threshold emmean SE df asymp.LCL asymp.UCL z.ratio p.value
0 1.390 0.215 Inf 0.968 1.81 6.462 <.0001
0.25 1.266 0.166 Inf 0.940 1.59 7.623 <.0001
0.5 1.350 0.186 Inf 0.985 1.71 7.250 <.0001
0.75 1.401 0.217 Inf 0.977 1.83 6.468 <.0001
1 0.917 0.203 Inf 0.518 1.32 4.509 <.0001
Results are given on the logit (not the response) scale.
Confidence level used: 0.95
$contrasts
contrast estimate SE df asymp.LCL
Deviant_threshold0 - Deviant_threshold0.25 0.1244 0.271 Inf -0.615
Deviant_threshold0 - Deviant_threshold0.5 0.0404 0.284 Inf -0.734
Deviant_threshold0 - Deviant_threshold0.75 -0.0112 0.305 Inf -0.842
Deviant_threshold0 - Deviant_threshold1 0.4733 0.296 Inf -0.333
Deviant_threshold0.25 - Deviant_threshold0.5 -0.0841 0.249 Inf -0.763
Deviant_threshold0.25 - Deviant_threshold0.75 -0.1357 0.272 Inf -0.878
Deviant_threshold0.25 - Deviant_threshold1 0.3489 0.262 Inf -0.366
Deviant_threshold0.5 - Deviant_threshold0.75 -0.0516 0.285 Inf -0.829
Deviant_threshold0.5 - Deviant_threshold1 0.4329 0.275 Inf -0.318
Deviant_threshold0.75 - Deviant_threshold1 0.4845 0.297 Inf -0.325
asymp.UCL z.ratio p.value
0.864 0.459 0.9909
0.815 0.142 0.9999
0.820 -0.037 1.0000
1.280 1.601 0.4970
0.595 -0.338 0.9972
0.606 -0.499 0.9875
1.064 1.331 0.6719
0.726 -0.181 0.9998
1.184 1.572 0.5155
1.294 1.633 0.4763
Results are given on the log odds ratio (not the response) scale.
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 5 estimates
P value adjustment: tukey method for comparing a family of 5 estimates Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
targetpair 12.4 12.4 1 91 0.0557 0.814
Deviant_threshold 13455.0 13455.0 1 91 60.2861 1.174e-11 ***
targetpair:Deviant_threshold 6012.1 6012.1 1 91 26.9379 1.269e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1$emtrends
targetpair Deviant_threshold.trend SE df lower.CL upper.CL t.ratio p.value
DN -52.7 6.15 91 -64.9 -40.49 -8.566 <.0001
NN -12.5 5.24 91 -22.9 -2.07 -2.382 0.0193
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio p.value
DN - NN -40.2 7.75 91 -55.6 -24.8 -5.190 <.0001
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95 # A tibble: 2 × 13
model term estimate std.error statistic p.value conf.low
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 below_.5 Deviant_threshold -16.0 11.3 -1.42 0.161 -38.6
2 above_.5 Deviant_threshold -11.3 11.2 -1.01 0.315 -33.8
conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <int> <int>
1 6.58 0.0335 0.0169 1 58 60
2 11.1 0.0206 0.000577 1 49 51# A tibble: 2 × 13
model term estimate std.error statistic p.value conf.low
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 below_.5 Deviant_threshold -12.1 18.7 -0.647 0.520 -49.6
2 above_.5 Deviant_threshold -17.1 15.4 -1.11 0.273 -48.2
conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <int> <int>
1 25.4 0.00717 -0.00995 1 58 60
2 13.9 0.0245 0.00456 1 49 51Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 1953 488.13 0.7195 0.5809
Residuals 86 58344 678.42 $emmeans
deviance emmean SE df lower.CL upper.CL t.ratio p.value
0 57.3 6.73 86 43.9 70.6 8.515 <.0001
0.25 48.0 5.21 86 37.7 58.4 9.222 <.0001
0.5 50.5 5.82 86 38.9 62.1 8.671 <.0001
0.75 49.9 6.73 86 36.5 63.2 7.415 <.0001
1 41.7 6.51 86 28.7 54.6 6.402 <.0001
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio p.value
deviance0 - deviance0.25 9.227 8.51 86 -14.5 32.9 1.085 0.8140
deviance0 - deviance0.5 6.767 8.90 86 -18.0 31.6 0.761 0.9411
deviance0 - deviance0.75 7.400 9.51 86 -19.1 33.9 0.778 0.9363
deviance0 - deviance1 15.579 9.36 86 -10.5 41.7 1.664 0.4613
deviance0.25 - deviance0.5 -2.460 7.81 86 -24.2 19.3 -0.315 0.9978
deviance0.25 - deviance0.75 -1.827 8.51 86 -25.5 21.9 -0.215 0.9995
deviance0.25 - deviance1 6.353 8.34 86 -16.9 29.6 0.762 0.9408
deviance0.5 - deviance0.75 0.633 8.90 86 -24.2 25.4 0.071 1.0000
deviance0.5 - deviance1 8.812 8.74 86 -15.5 33.2 1.009 0.8507
deviance0.75 - deviance1 8.179 9.36 86 -17.9 34.3 0.874 0.9058
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 5 estimates
P value adjustment: tukey method for comparing a family of 5 estimates | 0 (N=15) |
0.25 (N=25) |
0.5 (N=20) |
0.75 (N=15) |
1 (N=16) |
Overall (N=91) |
|
|---|---|---|---|---|---|---|
| pred_maj | ||||||
| Yes | 3 (20.0%) | 7 (28.0%) | 6 (30.0%) | 4 (26.7%) | 4 (25.0%) | 24 (26.4%) |
| No | 12 (80.0%) | 18 (72.0%) | 13 (65.0%) | 11 (73.3%) | 12 (75.0%) | 66 (72.5%) |
| Missing | 0 (0%) | 0 (0%) | 1 (5.0%) | 0 (0%) | 0 (0%) | 1 (1.1%) |
# A tibble: 4 × 14
# Groups: pred_maj [2]
pred_maj id term estimate std.error statistic p.value
<lgl> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 FALSE below_.5 Deviant_threshold -6.11 21.5 -0.285 0.777
2 FALSE above_.5 Deviant_threshold -21.6 18.4 -1.17 0.250
3 TRUE below_.5 Deviant_threshold -10.7 38.6 -0.276 0.786
4 TRUE above_.5 Deviant_threshold -13.2 32.0 -0.414 0.686
conf.low conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
1 -49.4 37.2 0.00197 -0.0224 1 41 43
2 -59.0 15.9 0.0387 0.0104 1 34 36
3 -93.4 72.1 0.00543 -0.0656 1 14 16
4 -82.9 56.4 0.0141 -0.0681 1 12 14Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 1981 495.34 0.7465 0.56319
pred_maj 1 2189 2189.21 3.2993 0.07305 .
deviance:pred_maj 4 2956 739.02 1.1138 0.35591
Residuals 80 53083 663.53
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1| 0 (N=15) |
0.25 (N=25) |
0.5 (N=20) |
0.75 (N=15) |
1 (N=16) |
Overall (N=91) |
|
|---|---|---|---|---|---|---|
| pns_med | ||||||
| High | 7 (46.7%) | 12 (48.0%) | 8 (40.0%) | 10 (66.7%) | 8 (50.0%) | 45 (49.5%) |
| Low | 8 (53.3%) | 13 (52.0%) | 12 (60.0%) | 5 (33.3%) | 8 (50.0%) | 46 (50.5%) |
# A tibble: 4 × 14
# Groups: pns_med [2]
pns_med id term estimate std.error statistic p.value
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 High below_.5 Deviant_threshold -16.1 32.2 -0.500 0.622
2 High above_.5 Deviant_threshold -22.3 21.8 -1.02 0.318
3 Low below_.5 Deviant_threshold -9.14 22.9 -0.400 0.692
4 Low above_.5 Deviant_threshold -15.5 22.5 -0.687 0.499
conf.low conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
1 -82.4 50.2 0.00989 -0.0297 1 25 27
2 -67.3 22.8 0.0415 0.00156 1 24 26
3 -55.8 37.5 0.00513 -0.0270 1 31 33
4 -62.1 31.1 0.0201 -0.0225 1 23 25Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 4 1953 488.13 0.6978 0.5957
pns_med 1 160 160.07 0.2288 0.6337
deviance:pns_med 4 1522 380.55 0.5440 0.7039
Residuals 81 56662 699.53 | 0 (N=91) |
1 (N=91) |
2 (N=91) |
3 (N=91) |
4 (N=91) |
5 (N=91) |
6 (N=91) |
7 (N=91) |
Overall (N=728) |
|
|---|---|---|---|---|---|---|---|---|---|
| trialnum | |||||||||
| 0 | 16 (17.6%) | 13 (14.3%) | 14 (15.4%) | 16 (17.6%) | 12 (13.2%) | 9 (9.9%) | 9 (9.9%) | 12 (13.2%) | 101 (13.9%) |
| 1 | 11 (12.1%) | 8 (8.8%) | 14 (15.4%) | 19 (20.9%) | 13 (14.3%) | 9 (9.9%) | 13 (14.3%) | 11 (12.1%) | 98 (13.5%) |
| 2 | 11 (12.1%) | 13 (14.3%) | 18 (19.8%) | 8 (8.8%) | 6 (6.6%) | 10 (11.0%) | 11 (12.1%) | 14 (15.4%) | 91 (12.5%) |
| 3 | 14 (15.4%) | 14 (15.4%) | 7 (7.7%) | 5 (5.5%) | 7 (7.7%) | 12 (13.2%) | 15 (16.5%) | 15 (16.5%) | 89 (12.2%) |
| 4 | 10 (11.0%) | 10 (11.0%) | 10 (11.0%) | 11 (12.1%) | 15 (16.5%) | 12 (13.2%) | 11 (12.1%) | 7 (7.7%) | 86 (11.8%) |
| 5 | 12 (13.2%) | 8 (8.8%) | 9 (9.9%) | 12 (13.2%) | 5 (5.5%) | 14 (15.4%) | 13 (14.3%) | 10 (11.0%) | 83 (11.4%) |
| 6 | 8 (8.8%) | 10 (11.0%) | 9 (9.9%) | 8 (8.8%) | 19 (20.9%) | 13 (14.3%) | 7 (7.7%) | 13 (14.3%) | 87 (12.0%) |
| 7 | 9 (9.9%) | 15 (16.5%) | 10 (11.0%) | 12 (13.2%) | 14 (15.4%) | 12 (13.2%) | 12 (13.2%) | 9 (9.9%) | 93 (12.8%) |